Usability Evaluation of a Novel Robotic Power Wheelchair for Indoor and Outdoor Navigation

Candiotti, Jorge; Kamaraj, Deepan C.; Daveler, Brandon; Chung, Chul; Grindle, Garrett G.; Cooper, Rosemarie

doi:10.1016/j.apmr.2018.07.432

Cited by 19 publications

(8 citation statements)

References 26 publications

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“…This section explains the curb negotiation capabilities of a mobility enhancement robot (MEBot), limitations, and the integration of the CRN system to improve the application. The MEBot was created as a testbed for advanced mobility applications to overcome environmental barriers [ 28 ]. The MEBot is a robotic wheelchair with six height-adjustable wheels and a modular drive wheel configuration.…”

Section: Methodsmentioning

confidence: 99%

“…Similar to RWs previously discussed, the MEBot must meet two assumptions prior to curb negotiation: the wheelchair must be aligned perpendicular to the curb for full contact of the wheels with the curb, and the curb height and approach angle must be known. These procedures were performed by the user as described in Figure 1 A. Usability evaluations with EPW users highlighted the challenges of curb alignment for safe negotiation [ 28 ].…”

Section: Methodsmentioning

confidence: 99%

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Automated Curb Recognition and Negotiation for Robotic Wheelchairs

Sivakanthan

Castagno

Candiotti

et al. 2021

Sensors

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Common electric powered wheelchairs cannot safely negotiate architectural barriers (i.e., curbs) which could injure the user and damage the wheelchair. Robotic wheelchairs have been developed to address this issue; however, proper alignment performed by the user is needed prior to negotiating curbs. Users with physical and/or sensory impairments may find it challenging to negotiate such barriers. Hence, a Curb Recognition and Negotiation (CRN) system was developed to increase user’s speed and safety when negotiating a curb. This article describes the CRN system which combines an existing curb negotiation application of a mobility enhancement robot (MEBot) and a plane extraction algorithm called Polylidar3D to recognize curb characteristics and automatically approach and negotiate curbs. The accuracy and reliability of the CRN system were evaluated to detect an engineered curb with known height and 15 starting positions in controlled conditions. The CRN system successfully recognized curbs at 14 out of 15 starting positions and correctly determined the height and distance for the MEBot to travel towards the curb. While the MEBot curb alignment was 1.5 ± 4.4°, the curb ascending was executed safely. The findings provide support for the implementation of a robotic wheelchair to increase speed and reduce human error when negotiating curbs and improve accessibility.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Automated Curb Recognition and Negotiation for Robotic Wheelchairs

Sivakanthan

Castagno

Candiotti

et al. 2021

Sensors

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“…Candiotti et al [3] compared conventional powered wheelchairs with their Mobility Enhancement roBotic (MEBot) wheelchair, which has six independently height-adjustable wheels for indoor and outdoor navigation. Twelve subjects with an average of 16.3 years of powered wheelchair driving experience participated in the study, which showed higher efficacy and safety of the MEBot, which come at the cost of higher mental demand on the users.…”

Section: Related Workmentioning

confidence: 99%

Usability Studies of an Egocentric Vision-Based Robotic Wheelchair

Kutbi

Xiaoxue

Chang

et al. 2020

J. Hum.-Robot Interact.

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Motivated by the need to improve the quality of life for the elderly and disabled individuals who rely on wheelchairs for mobility, and who may have limited or no hand functionality at all, we propose an egocentric computer vision based co-robot wheelchair to enhance their mobility without hand usage. The robot is built using a commercially available powered wheelchair modified to be controlled by head motion. Head motion is measured by tracking an egocentric camera mounted on the user's head and faces outward. Compared with previous approaches to hands-free mobility, our system provides a more natural human robot interface because it enables the user to control the speed and direction of motion in a continuous fashion, as opposed to providing a small number of discrete commands. This article presents three usability studies, which were conducted on 37 subjects. The first two usability studies focus on comparing the proposed control method with existing solutions while the third study was conducted to assess the effectiveness of training subjects to operate the wheelchair over several sessions. A limitation of our studies is that they have been conducted with healthy participants. Our findings, however, pave the way for further studies with subjects with disabilities. CCS Concepts: • Social and professional topics → Assistive technologies; • Computing methodologies → Computer vision; Computer vision tasks; • Human-centered computing → Interactive systems and tools;

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“…Advances in sensing technology have enabled researchers to design novel robotic EPWs that enhance mobility and accessibility. The Mobility Enhancement roBotic (MEBot) wheelchair was developed to address the mobility limitations of EPW users when facing hazardous environments with architectural barriers [22]. MEBot offers six height-adjustable wheels to control its seat orientation and elevation.…”

Section: Enav-mebot Fusionmentioning

confidence: 99%

Improving wheelchair route planning through instrumentation and navigation systems

Dzafic

Candiotti

Cooper

2020

2020 42nd Annual International Conference of the IEEE Engineering in Medicine &Amp; Biology Society (EMBC)

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Route planning is an important tool to reach points of interest. The current technology offers options for public transportation and pedestrians on the road and sidewalks, respectively. However, for people who use electric powered wheelchairs (EPW) as their primary means of mobility, the level of accessibility and EPW battery consumption are important during route planning. This paper introduces the concept of an accessible route navigation application to reduce EPW battery consumption. The application, called eNav, uses five layers of information including OpenStreetMaps (OSM), airborne laser scanner (ALS), Point-of-Interests (POIs), public transportation, and crowdsourcing. eNav collects these layers of information to provide the shortest, most accessible, and most comfortable routes that consume the least amount of EPW battery. Additionally, the paper presents the Mobility Enhancement roBot (MEBot), a legged-wheeled power wheelchair, to drive over architectural barriers and less accessible environments. The paper proposes the use of MEBot as a sixth layer of information to inform eNav and road authorities about sidewalk/route conditions, to improve road accessibility, and to provide an energy efficient route planning for non-MEBot users. Clinical Relevance-The eNav application offers the most energy efficient route to enhance EPW user's mobility.

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Usability Evaluation of a Novel Robotic Power Wheelchair for Indoor and Outdoor Navigation

Cited by 19 publications

References 26 publications

Automated Curb Recognition and Negotiation for Robotic Wheelchairs

Automated Curb Recognition and Negotiation for Robotic Wheelchairs

Usability Studies of an Egocentric Vision-Based Robotic Wheelchair

Improving wheelchair route planning through instrumentation and navigation systems

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